Estimating source-sink distributions and fluxes of reactive nitrogen and sulfur within a mixed forest canopy

The vertical source-sink distribution of air pollutants within and above forested canopies is necessary for describing the biological, physical, and chemical processes influencing the soil-vegetation-atmosphere exchange. This study implemented inverse modeling methods to estimate the source-sink and flux profiles of reactive ni-trogen (N) and sulfur (S) compounds from measurements of the mean concentration profiles of ammonia (NH3), nitric acid (HNO3), sulfur dioxide (SO2), and particulate ammonium (NH4+), nitrate (NO3), and sulfate (SO42-) at a forest site in the southern Appalachian Mountains. Three inverse approaches utilizing different approximations to scalar transport within the canopy were developed and evaluated against sensible heat flux measurements. The Eulerian model (EUL), which incorporates vertical velocity skewness, performed well in reproducing the turbulent heat fluxes and was subsequently used to calculate the chemical source-sink and flux profiles. Above-canopy fluxes of NH3 were downward, indicating that the forest was a net sink of NH3. The soil/litter layer was both a source and a sink for NH3 but the exchange rate at the forest floor was small. Fluxes of HNO3, SO2, NO3-, NH4+, and SO42- were uni-directional (deposition only) between the air and the canopy/ground and increased monotonically from the forest floor to the canopy top. Crown foliage dominated the uptake of reactive N and S during the growing season, accounting for 80-90% of the total canopy-scale flux. Fluxes and canopy-ground partitioning estimated using the resistance-based Surface Tiled Aerosol and Gas Exchange (STAGE) model were generally comparable to EUL. The comparison highlights the need for improved parameterizations of litter exchange and NH3 compensation points in resistance models for forest ecosystems. The findings here benefit the application of critical loads in forest ecosystems and guide further development of resistance-based exchange models.